Attachment Styles and AI Attachment among Medical and Paramedical Students: The Role of Emotion Regulation and Social Support

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DOI: hhttps://doi.org/10.5281/zenodo.22302365

Shahina L. and Annalakshmi N. (Department of Psychology, Bharathiar University, Coimbatore, Tamil Nadu)

In the rapidly evolving and technologically advanced environment of higher education, Medical and paramedical students are exposed to multiple academic, personal, and psychological challenges that influence their well-being, interpersonal functioning, and academic performance, often leading to stress and emotional difficulties. The present study aimed to examine adult attachment and AI attachment among medical and paramedical students, with a focus on the predictive role of difficulties in emotion regulation and social support among Nandha Educational Institutions in Erode. A sample of 658 medical and paramedical students in Tamil Nadu was examined using self-report tools for adult attachment (Sithara & Annalakshmi, 2024), AI attachment (Kasturiratna & Hartanto, 2025), emotion regulation difficulties (Victor & Klonsky, 2016), and perceived social support (Zimet et al., 1988). Statistical techniques such as descriptive statistics, Pearson’s correlation, one-way ANOVA, and regression analysis were carried out for analyzing the data. After removing students with multiple dominant attachment styles (N = 594), fearful and preoccupied attachment styles predicted higher emotional closeness and social substitution, dismissive attachment showed moderate AI attachment, and secure attachment showed the lowest. Multiple regression indicated that difficulties in emotion regulation significantly predicted AI attachment, whereas perceived social support did not, suggesting that individual psychological factors and attachment patterns, rather than demographic or contextual variables, primarily drive engagement and reliance on AI systems. Implications for educational interventions and welfare of the students are discussed.